Dataset Information

Combinatorial metabolic engineering of Pseudomonas putida KT2440 for efficient mineralization of 1,2,3-trichloropropane.

ABSTRACT: An industrial waste, 1,2,3-trichloropropane (TCP), is toxic and extremely recalcitrant to biodegradation. To date, no natural TCP degraders able to mineralize TCP aerobically have been isolated. In this work, we engineered a biosafety Pseudomonas putida strain KT2440 for aerobic mineralization of TCP by implantation of a synthetic biodegradation pathway into the chromosome and further improved TCP mineralization using combinatorial engineering strategies. Initially, a synthetic pathway composed of haloalkane dehalogenase, haloalcohol dehalogenase and epoxide hydrolase was functionally assembled for the conversion of TCP into glycerol in P. putida KT2440. Then, the growth lag-phase of using glycerol as a growth precursor was eliminated by deleting the glpR gene, significantly enhancing the flux of carbon through the pathway. Subsequently, we improved the oxygen sequestering capacity of this strain through the heterologous expression of Vitreoscilla hemoglobin, which makes this strain able to mineralize TCP under oxygen-limited conditions. Lastly, we further improved intracellular energy charge (ATP/ADP ratio) and reducing power (NADPH/NADP+ ratio) by deleting flagella-related genes in the genome of P. putida KT2440. The resulting strain (named KTU-TGVF) could efficiently utilize TCP as the sole source of carbon for growth. Degradation studies in a bioreactor highlight the value of this engineered strain for TCP bioremediation.

SUBMITTER: Gong T

PROVIDER: S-EPMC5539299 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Combinatorial metabolic engineering of Pseudomonas putida KT2440 for efficient mineralization of 1,2,3-trichloropropane.

Gong Ting T Xu Xiaoqing X Che You Y Liu Ruihua R Gao Weixia W Zhao Fengjie F Yu Huilei H Liang Jingnan J Xu Ping P Song Cunjiang C Yang Chao C

Scientific reports 20170801 1

An industrial waste, 1,2,3-trichloropropane (TCP), is toxic and extremely recalcitrant to biodegradation. To date, no natural TCP degraders able to mineralize TCP aerobically have been isolated. In this work, we engineered a biosafety Pseudomonas putida strain KT2440 for aerobic mineralization of TCP by implantation of a synthetic biodegradation pathway into the chromosome and further improved TCP mineralization using combinatorial engineering strategies. Initially, a synthetic pathway composed ...[more]

PMID: 28765600

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Project description:BackgroundPseudomonas putida is a promising candidate for the industrial production of biofuels and biochemicals because of its high tolerance to toxic compounds and its ability to grow on a wide variety of substrates. Engineering this organism for improved performances and predicting metabolic responses upon genetic perturbations requires reliable descriptions of its metabolism in the form of stoichiometric and kinetic models.ResultsIn this work, we developed kinetic models of P. putida to predict the metabolic phenotypes and design metabolic engineering interventions for the production of biochemicals. The developed kinetic models contain 775 reactions and 245 metabolites. Furthermore, we introduce here a novel set of constraints within thermodynamics-based flux analysis that allow for considering concentrations of metabolites that exist in several compartments as separate entities. We started by a gap-filling and thermodynamic curation of iJN1411, the genome-scale model of P. putida KT2440. We then systematically reduced the curated iJN1411 model, and we created three core stoichiometric models of different complexity that describe the central carbon metabolism of P. putida. Using the medium complexity core model as a scaffold, we generated populations of large-scale kinetic models for two studies. In the first study, the developed kinetic models successfully captured the experimentally observed metabolic responses to several single-gene knockouts of a wild-type strain of P. putida KT2440 growing on glucose. In the second study, we used the developed models to propose metabolic engineering interventions for improved robustness of this organism to the stress condition of increased ATP demand.ConclusionsThe study demonstrates the potential and predictive capabilities of the kinetic models that allow for rational design and optimization of recombinant P. putida strains for improved production of biofuels and biochemicals. The curated genome-scale model of P. putida together with the developed large-scale stoichiometric and kinetic models represents a significant resource for researchers in industry and academia.

Project description:Pseudomonas putida KT2440 has received increasing attention as an important biocatalyst for the conversion of diverse carbon sources to multiple products, including the olefinic diacid, cis,cis-muconic acid (muconate). P. putida has been previously engineered to produce muconate from glucose; however, periplasmic oxidation of glucose causes substantial 2-ketogluconate accumulation, reducing product yield and selectivity. Deletion of the glucose dehydrogenase gene (gcd) prevents 2-ketogluconate accumulation, but dramatically slows growth and muconate production. In this work, we employed adaptive laboratory evolution to improve muconate production in strains incapable of producing 2-ketogluconate. Growth-based selection improved growth, but reduced muconate titer. A new muconate-responsive biosensor was therefore developed to enable muconate-based screening using fluorescence activated cell sorting. Sorted clones demonstrated both improved growth and muconate production. Mutations identified by whole genome resequencing of these isolates indicated that glucose metabolism may be dysregulated in strains lacking gcd. Using this information, we used targeted engineering to recapitulate improvements achieved by evolution. Deletion of the transcriptional repressor gene hexR improved strain growth and increased the muconate production rate, and the impact of this deletion was investigated using transcriptomics. The genes gntZ and gacS were also disrupted in several evolved clones, and deletion of these genes further improved strain growth and muconate production. Together, these targets provide a suite of modifications that improve glucose conversion to muconate by P. putida in the context of gcd deletion. Prior to this work, our engineered strain lacking gcd generated 7.0 g/L muconate at a productivity of 0.07 g/L/h and a 38% yield (mol/mol) in a fed-batch bioreactor. Here, the resulting strain with the deletion of hexR, gntZ, and gacS achieved 22.0 g/L at 0.21 g/L/h and a 35.6% yield (mol/mol) from glucose in similar conditions. These strategies enabled enhanced muconic acid production and may also improve production of other target molecules from glucose in P. putida.

Project description:BACKGROUND: Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. RESULTS: We present a genome-scale reconstruction of P. putida KT2440's metabolism, iJN746, which was constructed based on genomic, biochemical, and physiological information. This manually-curated reconstruction accounts for 746 genes, 950 reactions, and 911 metabolites. iJN746 captures biotechnologically relevant pathways, including polyhydroxyalkanoate synthesis and catabolic pathways of aromatic compounds (e.g., toluene, benzoate, phenylacetate, nicotinate), not described in other metabolic reconstructions or biochemical databases. The predictive potential of iJN746 was validated using experimental data including growth performance and gene deletion studies. Furthermore, in silico growth on toluene was found to be oxygen-limited, suggesting the existence of oxygen-efficient pathways not yet annotated in P. putida's genome. Moreover, we evaluated the production efficiency of polyhydroxyalkanoates from various carbon sources and found fatty acids as the most prominent candidates, as expected. CONCLUSION: Here we presented the first genome-scale reconstruction of P. putida, a biotechnologically interesting all-surrounder. Taken together, this work illustrates the utility of iJN746 as i) a knowledge-base, ii) a discovery tool, and iii) an engineering platform to explore P. putida's potential in bioremediation and bioplastic production.

Dataset Information

Combinatorial metabolic engineering of Pseudomonas putida KT2440 for efficient mineralization of 1,2,3-trichloropropane.

Publications

Combinatorial metabolic engineering of Pseudomonas putida KT2440 for efficient mineralization of 1,2,3-trichloropropane.

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